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Record W7044049159

UNDERSTANDING RESILIENCE AND SETTLEMENT IN REFUGEE YOUTH: A CRITICAL NARRATIVE STUDY

2011· article· en· W7044049159 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2011
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeSettlement (finance)Psychological resilienceNarrativeResilience (materials science)Qualitative research
DOInot available

Abstract

fetched live from OpenAlex

This study seeks to explore the resilience and settlement of refugee youth through critical narrative. Objectives of this study are: (1) to explore the facilitators and barriers of the resettlement phase of youth refugees and to identify ways in which services and policies can better facilitate youth refugees' successful transitions to Ontario, Canada, according to the teenagers themselves and, (2) to explore in brief youth refugees' health status throughout the resettlement process, according to their own perspectives. This study explores the literature to date of refugee youth and settlement issues, assesses the pros and cons of the use of visual methodologies, specifically the use of body mapping with refugee youth, presents critical narratives of the participants, and provides implications for further research and practice. Findings suggest that time for body mapping interviews was greater than envisioned; there were no major health concerns among participants and; education, relationships with family and friends, faith, and hope for the future are key contributors to the resilience of refugee youth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0140.013
Scholarly communication0.0070.007
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.334
GPT teacher head0.403
Teacher spread0.069 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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